Ji Songbai, Zhao Wei
Thayer School of Engineering, Dartmouth College, 14 Engineering Drive, Hanover, NH, 03755, USA,
Ann Biomed Eng. 2015 Aug;43(8):1877-95. doi: 10.1007/s10439-014-1193-3. Epub 2014 Dec 2.
Finite element models of the human head play an important role in investigating the mechanisms of traumatic brain injury, including sports concussion. A critical limitation, however, is that they incur a substantial computational cost to simulate even a single impact. Therefore, current simulation schemes significantly hamper brain injury studies based on model-estimated tissue-level responses. In this study, we present a pre-computed brain response atlas (pcBRA) to substantially increase the simulation efficiency in estimating brain strains using isolated rotational acceleration impulses parameterized with four independent variables (peak magnitude and duration, and rotational axis azimuth and elevation angles) with values determined from on-field measurements. Using randomly generated testing datasets, the partially established pcBRA achieved a 100% success rate in interpolation based on element-wise differences in accumulated peak strain ([Formula: see text]) according to a "double-10%" criterion or average regional [Formula: see text] in generic regions and the corpus callosum. A similar performance was maintained in extrapolation. The pcBRA performance was further successfully validated against directly simulated responses from two independently measured typical real-world rotational profiles. The computational cost to estimate element-wise whole-brain or regional [Formula: see text] was 6 s and <0.01 s, respectively, vs. ~50 min directly simulating a 40 ms impulse. These findings suggest the pcBRA could substantially increase the throughput in impact simulation without significant loss of accuracy from the estimation itself and, thus, its potential to accelerate the exploration of the mechanisms of sports concussion in general. If successful, the pcBRA may also become a diagnostic adjunct in conjunction with sensors that measure head impact kinematics on the field to objectively monitor and identify tissue-level brain trauma in real-time for "return-to-play" decision-making on the sideline.
人体头部的有限元模型在研究创伤性脑损伤机制（包括运动性脑震荡）中发挥着重要作用。然而，一个关键的局限性在于，即使模拟单次撞击，它们也会产生高昂的计算成本。因此，当前的模拟方案严重阻碍了基于模型估计的组织水平反应的脑损伤研究。在本研究中，我们提出了一种预先计算的脑反应图谱（pcBRA），以显著提高使用由四个独立变量（峰值大小和持续时间，以及旋转轴方位角和仰角）参数化的孤立旋转加速度脉冲来估计脑应变的模拟效率，这些变量的值由现场测量确定。使用随机生成的测试数据集，部分建立的pcBRA根据“双10%”标准或通用区域和胼胝体中的平均区域累积峰值应变（[公式：见正文]），基于元素级差异在插值中实现了100%的成功率。在外推中也保持了类似的性能。pcBRA的性能通过与来自两个独立测量的典型真实世界旋转轮廓的直接模拟反应进行比较，进一步得到了成功验证。估计元素级全脑或区域累积峰值应变（[公式：见正文]）的计算成本分别为(6)秒和(<0.01)秒，而直接模拟一个(40)毫秒的脉冲则约需(50)分钟。这些发现表明，pcBRA可以显著提高撞击模拟的通量，而不会因估计本身而导致显著的精度损失，因此，它有可能加速对一般运动性脑震荡机制的探索。如果成功，pcBRA还可能与现场测量头部撞击运动学的传感器结合，成为一种诊断辅助工具，以客观地实时监测和识别组织水平的脑损伤，用于在边线进行“重返比赛”的决策。
